Question Answering
Transformers
Safetensors
English
qwen2
text-generation
biology
medical
healthcare
text-generation-inference
Instructions to use HPAI-BSC/Qwen2.5-Aloe-Beta-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPAI-BSC/Qwen2.5-Aloe-Beta-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="HPAI-BSC/Qwen2.5-Aloe-Beta-7B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("HPAI-BSC/Qwen2.5-Aloe-Beta-7B") model = AutoModelForCausalLM.from_pretrained("HPAI-BSC/Qwen2.5-Aloe-Beta-7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8acac31337b78f9a45dbeaafc21a6797ab84d416ccd11867c6ea477219b5e8c1
- Size of remote file:
- 1.09 GB
- SHA256:
- 3bdce26955505317ede5ca257a333308a919734c7119ae2c25da59f24ec43ebe
路
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